Samsung Galaxy S24 Ultra
Geekbench AI Score
461
Single Precision Score
457
Half Precision Score
1021
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | markman |
| Upload Date | June 08 2025 03:58 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928U |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.83 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
309
57.5 IPS |
|
|
Image Classification (HP)
|
100% |
310
57.7 IPS |
|
|
Image Classification (Q)
|
99% |
809
150.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
394
6.39 IPS |
|
|
Image Segmentation (HP)
|
100% |
395
6.40 IPS |
|
|
Image Segmentation (Q)
|
98% |
813
13.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
535
0.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
518
0.60 IPS |
|
|
Pose Estimation (Q)
|
98% |
1964
2.30 IPS |
|
|
Object Detection (SP)
|
100% |
288
22.8 IPS |
|
|
Object Detection (HP)
|
100% |
288
22.9 IPS |
|
|
Object Detection (Q)
|
87% |
819
65.7 IPS |
|
|
Face Detection (SP)
|
100% |
695
8.26 IPS |
|
|
Face Detection (HP)
|
100% |
703
8.35 IPS |
|
|
Face Detection (Q)
|
97% |
1676
20.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
625
4.81 IPS |
|
|
Depth Estimation (HP)
|
99% |
625
4.81 IPS |
|
|
Depth Estimation (Q)
|
64% |
1293
11.7 IPS |
|
|
Style Transfer (SP)
|
100% |
905
1.16 IPS |
|
|
Style Transfer (HP)
|
100% |
827
1.06 IPS |
|
|
Style Transfer (Q)
|
98% |
2019
2.60 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
290
10.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
288
10.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
958
35.5 IPS |
|
|
Text Classification (SP)
|
100% |
353
471.1 IPS |
|
|
Text Classification (HP)
|
100% |
363
483.9 IPS |
|
|
Text Classification (Q)
|
91% |
601
807.4 IPS |
|
|
Machine Translation (SP)
|
100% |
583
10.0 IPS |
|
|
Machine Translation (HP)
|
100% |
579
9.98 IPS |
|
|
Machine Translation (Q)
|
57% |
463
11.3 IPS |
